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https://github.com/zeyad-mansour/lunar
a neural network aim assist that uses real-time object detection accelerated with CUDA on Nvidia GPUs
https://github.com/zeyad-mansour/lunar
aimbot cheat cod csgo detection fortnite hack lunar neural-network-aimbot python softaim splitgate undetected valorant warzone yolov5
Last synced: 12 days ago
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a neural network aim assist that uses real-time object detection accelerated with CUDA on Nvidia GPUs
- Host: GitHub
- URL: https://github.com/zeyad-mansour/lunar
- Owner: zeyad-mansour
- License: gpl-3.0
- Created: 2021-04-12T16:53:26.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-04-14T15:54:24.000Z (about 1 year ago)
- Last Synced: 2024-02-29T11:31:08.909Z (4 months ago)
- Topics: aimbot, cheat, cod, csgo, detection, fortnite, hack, lunar, neural-network-aimbot, python, softaim, splitgate, undetected, valorant, warzone, yolov5
- Language: Python
- Homepage: https://discord.gg/5n6vS95jWp
- Size: 221 MB
- Stars: 392
- Watchers: 17
- Forks: 124
- Open Issues: 173
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Lists
- awesome-yolo-object-detection - zeyad-mansour/lunar - mansour/lunar?style=social"/> : Lunar is a neural network aimbot that uses real-time object detection accelerated with CUDA on Nvidia GPUs. (Applications)
README
# Lunar
Lunar is a neural network aim assist that uses real-time object detection accelerated with CUDA on Nvidia GPUs.
## About
Lunar can be modified to work with a variety of FPS games; however, it is currently configured for Fortnite. Besides being general purpose, the main advantage of using Lunar is that it does not meddle with the memory of other processes.
The basis of Lunar's player detection is the [YOLOv5](https://github.com/ultralytics/yolov5) architecture written in PyTorch.
A demo video (outdated) can be found [here](https://www.youtube.com/watch?v=XDAcQNUuT84).
## Installation
1. Install a version of [Python](https://www.python.org/downloads/) 3.8 or later.
2. Navigate to the root directory. Use the package manager [pip](https://pip.pypa.io/en/stable/) to install the necessary dependencies.
```
pip install -r requirements.txt
```
## Usage
```
python lunar.py
```
To update sensitivity settings:
```
python lunar.py setup
```
To collect image data for annotating and training:
```
python lunar.py collect_data
```
## Issues
- The method of mouse movement ([SendInput](https://github.com/zeyad-mansour/Lunar/blob/45e05373036f8bd072667313c155e55735cd7f57/lib/aimbot.py#L126)) is slow. For this reason, the crosshair often lags behind a moving detection. This problem can be lessened by increasing the [pixel_increment](https://github.com/zeyad-mansour/Lunar/blob/45e05373036f8bd072667313c155e55735cd7f57/lib/aimbot.py#L56) (e.g. to 4) so fewer calls to that function are made.
- False positives can also happen under certain lighting conditions.
## Contributing
Pull requests are welcome. If you have any suggestions, questions, or find any issues, please open an [issue](https://github.com/zeyad-mansour/Lunar/issues) and provide some detail.
If you find this project interesting or helpful, please star the repository.
## License
This project is distributed under [GNU General Public License v3.0](https://github.com/zeyad-mansour/Lunar/blob/main/LICENSE) license.